Adaptation to stress in football athletes: the importance of cognitive appraisal

fpsyg-13-939840 August 24, 2022 Time: 14:11 # 1 TYPE Original Research PUBLISHED 24 August 2022 DOI 10.3389/fpsyg.2022.939840 OPEN ACCESS EDITED BY Carla Meijen, St Mary’s University, Twickenham, United Kingdom REVIEWED BY Jamel Hajji, Tunis University, Tunisia John Elvis Hagan Jr., Bielefeld University, Germany *CORRESPONDENCE A. Rui Gomes [email protected] SPECIALTY SECTION This article was submitted to Movement Science and Sport Psychology, a section of the journal Frontiers in Psychology RECEIVED 09 May 2022 ACCEPTED 27 July 2022 PUBLISHED 24 August 2022 CITATION Gomes AR, Simães C, Morais C and Cunha R (2022) Adaptation to stress in football athletes: The importance of cognitive appraisal. Front. Psychol. 13:939840. doi: 10.3389/fpsyg.2022.939840 COPYRIGHT © 2022 Gomes, Simães, Morais and Cunha. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Adaptation to stress in football athletes: The importance of cognitive appraisal A. Rui Gomes1*, Clara Simães2,3, Catarina Morais4and Ricardo Cunha1 1Psychology Research Centre, School of Psychology, University of Minho, Braga, Portugal, 2School of Nursing, University of Minho, Braga, Portugal, 3Health Sciences Research Unit: Nursing (UICISA: E), Nursing School of Coimbra (ESEnfC), Coimbra, Portugal, 4Research Centre for Human Development, Faculty of Education and Psychology, Universidade Católica Portuguesa, Porto, Portugal This study analysed the adaptation of football athletes to competitive stressors regarding the upcoming match. For that, the study adopted a crosssectional methodology using a critical incident approach. The participants were 352 young male football athletes, aged between 15 and 19 years (M= 16.91, SD = 0.99), who were competing in the national football championship. The results indicated that cognitive appraisal partially mediated the relationship between competitive stressors and emotions: athletes who perceived stressors as a challenge, tended to feel more control over the situation and more resourceful (coping perception), leading to a more positive emotional experience, while those perceiving the stressors as a threat were more prone to experience less control and more negative emotions. This mediation model was moderated by athletes’ competitive level (U17 or U19), as the role of challenge perception was more pronounced in the U19 team, while the relationship between threat perception and less control was only observed for the U17 team. In sum, the data reveals the importance of cognitive appraisal in young football athletes’ adaptation to competitive stressors, bolstering the theoretical models in this area and the importance of psychologists to consider these variables during intervention, particularly cognitive appraisal. KEYWORDS challenge perception, competitive stressors, emotions, competitive level, threat perception, stress, age, sporting level Introduction Stress is a prominent topic in daily life because of its impact on individuals’ living contexts, being well-known some harmful effect on physical and mental health (Cohen et al.,2007;Gomes,2014;Monroe and Slavich,2016). Stress can be understood as a set of negative reactions and feelings in response to adverse or demanding situations (Turner and Jones,2014), depending on how one evaluates and deals with it, representing one of Frontiers in Psychology 01 frontiersin.org fpsyg-13-939840 August 24, 2022 Time: 14:11 # 2 Gomes et al. 10.3389/fpsyg.2022.939840 the main factors contributing to reduced sports performance (McGreary et al.,2020). In recent decades, a growing interest has been observed in the phenomenon of adaptation to stress in the sports context due to the demands placed on athletes who perform in top-level competitive sports that justify the stressful nature of this context (Barker et al.,2011;Gustafsson et al.,2017;Hase et al.,2019;McLoughlin et al.,2021). Although youth sport represents a positive contribution to physical and psychological health (Krustrup et al.,2010;Snyder et al.,2010;Strand et al.,2019), it has also been associated with negative effects, such as anxiety, fear of failure, reduced self-confidence, and burnout (Choi et al.,2014;Gustafsson et al.,2017). Thus, it is relevant to understand how young athletes adapt to stress in sports contexts and the role of psychological factors in how they evaluate and cope with potential stressors. The study of adaptation to stress and underlying factors is well described by Lazarus (1991),Lazarus (1999)in the Transactional Stress Model, which suggested that the adaptation process should be analyzed considering cognitive, motivational, and relational factors. Specifically, the author argues that a comprehensive analysis of adaption to stress should consider simultaneously the stressors that trigger the situation, how the situation is evaluated by the individual (cognitive appraisal), and the feelings that emerge from the situation. In other words, there are four key variables involved in the adaptive process: the stressors, the cognitive appraisal of the stressful situation, the athletes’ ability to cope with stress, and the emotions arising from those situations. Regarding stressors, there is evidence that athletes face numerous stressors, as is the case of pressure to perform, social expectations, fear of opponents or injuries, fear of making mistakes, among others (cf. Arnold and Fletcher,2012 for a review); however, it seems that it is not the presence of the stressors itself that leads to negative experiences being necessary to consider the processes of cognitive appraisal. According to the Transactional Model of Lazarus (1991), cognitive appraisal consists of two components: (1) primary cognitive appraisal, in which the individual attributes meaning to the stressful situation, checking whether it is according personal goals, values, and beliefs; and, (2) secondary cognitive appraisal, in which the individual analyses the personal resources to deal with the stressful situation. Regarding the primary cognitive appraisal, which occurs once the athlete evaluates a situation as stressful, four types of appraisal can arise: (a) challenge, in which the athlete appraises the situation as stimulating and anticipates gains; (b) threat, in which the athlete anticipates that something negative may occur in the future; (c) benefit, in which the athlete identifies the situation as advantageous; and, (c) loss or damage, in which the athlete identifies the situation as harmful or damaging (Lazarus and Folkman,1984). Next, the athlete will try to deal with the stressors by engaging in secondary cognitive appraisal and, therefore, analyzes: (a) the external vs. internal responsibility of the event; (b) coping in terms of personal resources to cope with the demands of the event; (c) control regarding the stressful event; and, (d) future expectations, that is the extent to which the situation can change for the better or worse, taking into account the athletes’ personal goals (Lazarus,1991;Gomes,2014). Taken together, it is possible to conclude that it is the cognitive appraisal of the situation, and not the situation itself, that determines the experience of stress (Dixon and Turner,2018). This distinction of variables involved in cognitive appraisal has been studied in sports contexts. For example, Campbell and Jones (2002) found that stressors can be appraised in different ways (as challenging, threatening, harmful), depending on how athletes interpret the situation. Specifically, they demonstrated that athletes who perceive the stressor as a challenge also perceived more control over the situation; on the other hand, the stress levels were more severe when it was perceived as threatening or harmful. The analysis of how athletes appraise the stressors allows for a deeper understanding of the stress experience (McGreary et al.,2020), which, in turn, can explain the subsequent impact on emotions and performance achieved by athletes. Some research that analyzed the relationship between emotions and performance in athletes (e.g., Lane et al.,2009,2010;González-García and Martinent,2020) suggested that positive emotional and psychological states, such as happiness, calm, and confidence, were associated with optimal performance (achievement of an important goal), whereas negative emotional and psychological states (e.g., anger and confusion) were associated with a dysfunctional performance and failure to achieve an important goal. These studies allow an understanding of the factors involved in the process of adaptation to stress; however, it is difficult to capture the whole experience of stress just by analyzing parts of the adaptation process, which reinforces the importance of capturing this process in an integrated way (Nicholls et al.,2012;Wong et al.,2015;Gomes,2017). Thus, this study aims to provide an integrative framework to understand adaptation to stressors on young athletes by taking an integrative analysis of competitive stressors, cognitive appraisal of a stressful situation, and the arising emotions of the stressful situation, considering, at the same time, the athletes’ characteristics (i.e., competitive level) that can influence the cognitive processing of stressful situations and, consequently, the adaptation process. Stressors, cognitive appraisal, and emotions The relations established between stressors, cognitive appraisal, and the emotions associated with the stressful Frontiers in Psychology 02 frontiersin.org fpsyg-13-939840 August 24, 2022 Time: 14:11 # 3 Gomes et al. 10.3389/fpsyg.2022.939840 experience have been considered by transactional (Lazarus, 1991) and interactive (Gomes,2014) proposals of adaptation to stress. Specifically, this study analyses the relations between these variables in sequential conceptual logic. The first variable refers to competitive stressors organized in six dimensions (competitive readiness, performance, errors, social expectations, opponents, and injuries). The second variable was cognitive appraisal, which refers to how athletes interpret a stressful event. Cognitive appraisal is a pivotal variable in the adaptation to stress because negative reactions occur when the individual evaluates the external demands of a situation as exceeding their abilities and resources to cope with those same demands (Lazarus,1991). Building upon Lazarus’ theoretical model, Gomes (2014)proposed the Interactive Model of Adaptation to Stress. This theoretical framework expands Lazarus’ Transactional Stress Model, specifically by arguing that an adaptation process will only begin if the individual considers the stressors as important for their personal goals. For this reason, athletes’ perception of the importance of the stressful situation (i.e., competitive match) was measured in this study to ensure that it only reported results from athletes who attributed some personal meaning to the situation they were involved in, so they could then assess primary (e.g., threat and challenge perceptions) and secondary (e.g., coping and control perceptions) cognitive appraisal of the competitive stressors. The process of cognitive appraisal has consequences on athletes’ emotions, which represents the third variable in the analysis in this study. Emotions are understood as psychophysiological reactions resulting from the interaction with the environment, being inherently linked to cognitive appraisal (Lazarus,2000;Tamminen et al.,2016). In fact, cognitive appraisal influences the quality and intensity of the emotions experienced during a stressful event, which in turn influences behavior and athletes’ performance (Lazarus and Folkman,1991;Jones,1995). In the sports context, there are indications that if the athlete appraises the situation as threatening or harmful, they will tend to experience negative emotions; while if the athlete appraises the situation as challenging or beneficial, they will tend to experience positive emotions (Nicholls et al.,2014;Meijen et al.,2019). In addition, the influence of the secondary cognitive appraisal needs to be considered since low future expectations and low coping perceptions may intensify negative emotions, whereas high future expectations and high coping perceptions may intensify positive emotions (Lazarus,1991,2000;Collins, 2019). In sum, this study comprises three variables that are central in the understanding of human adaptation to stress, and their role in the analysis was conceptually determined: competitive stressors (i.e., sources of stress) were conceived as antecedent variables (predictor variable), the cognitive appraisal was as a mediator, and emotions were as a consequent variable (criterion variable). Thus, it is expected that: H1. The relationship between competitive stressors and emotions is mediated by primary and secondary cognitive appraisal. Specifically, it is expected a negative pattern of adaptation to stressors in this way: (a) higher perception of stressors predicts negative patterns of cognitive appraisal (lower challenge and higher threat perception, lower control, and coping), which, in turn, predicts a more negative emotional experience and a less positive emotional experience; and it is expected a positive pattern of adaptation to stressors in this way: (b) lower perception of stressors predicts positive patterns of cognitive appraisal (higher challenge and lower threat perceptions, higher control and coping), which, in turn, predicts a more positive and less negative emotional experience. The moderating role of competitive level Some studies indicate that the relationship between cognitive appraisal and emotions is not as linear and automatic as previously thought (e.g., Uphill and Jones,2007;Nicholls et al.,2011). Thus, it is possible that other factors, such as the athletes’ personal attributes and sports characteristics, interfere in the relationship between stressors, cognitive appraisal, and emotions and can, consequently, influence the process of adaptation to stress. The Interactive Model of Adaptation to Stress (Gomes,2014) refers to these aspects as antecedent factors and suggests that athletes’ characteristics (such as gender, age, competitive level, etc.) can influence how individuals appraise stressors and, consequently, can have an impact on their adaptation to stress. The author proposed that athletes’ characteristics should be analyzed as possible moderating variables of the relationship between stressors and the outcome of stress adaptation. Indeed, previous literature has found significant age differences in how athletes perceive and deal with stressful events in sports contexts. For example, Martens et al. (1990) wrote a literature review in which they concluded that competitive trait anxiety is age-related, arguing that younger children, when compared to older athletes, experience less anxiety regarding their participation in casual sports (such as playground matches) but more trait anxiety in structured sports settings. According to the authors, this is due to the awareness of the competitive nature of these situations (not salient in the playground, but very explicit when playing a formal competition). However, there are also indications that younger athletes report higher sport-related anxiety than their older teammates (e.g., Wong and Bridges,1994). Frontiers in Psychology 03 frontiersin.org fpsyg-13-939840 August 24, 2022 Time: 14:11 # 4 Gomes et al. 10.3389/fpsyg.2022.939840 Reeves et al. (2009)provided additional indications suggesting that even though some stressors are similar across ages (e.g., making errors, performance), older adolescents show a greater number and wider range of coping strategies compared to younger adolescents. At the same time, older adolescents tend to use more problemand emotion-focused strategies and fewer avoidance strategies when compared to younger adolescents (Goyen and Anshel,1998;Reeves et al.,2009). These results are consistent with the ones found by Bebetsos and Antoniou (2003), who reported that older badminton athletes cope better with psychological distress and report higher emotional selfcontrol. These results suggest that the age group needs to be considered and that older athletes may have gained, through experience, greater coping strategies and, therefore, are more proficient in dealing with stressful situations, such as sports competitions. In our study, we analyzed the role of age by collecting data from two competitive levels (athletes until 17 years old and athletes until 19 years old). This option allowed the division of athletes according to the competitive demands that are formally established by the respective national federation. Therefore, it is expected that: H2. The relationship between competitive stressors and emotions is mediated by primary and secondary cognitive appraisal (as stated in H1) and is moderated by athletes’ competitive level (U17 and U19). Specifically, it is expected that the negative pattern of adaptation to stressors predicted on H1 (lower challenge and higher threat perception, lower control and coping) is stronger in younger athletes (U17), and the positive pattern of adaptation to stressors (higher challenge and lower threat perceptions, higher control and coping) is stronger on older athletes (U19). In sum, filling an important gap in the literature (Nicholls et al.,2012;Wong et al.,2015;Gomes,2017) by pursuing a comprehensively investigating of the process of adaptation to competitive stressors, this study sought to analyze (1) the mediating role of cognitive appraisal in the relationship between competitive stressors and emotional experience; and (2) the moderating role of competitive level in the relationship between competitive stressors, cognitive appraisal, and emotions (cf. Figure 1). Based on the theoretical proposals formulated previously (cf. Lazarus,1991,1999;Gomes,2014), we seek to understand how athletes adapt, evaluate, and react to a specific stressful situation in sport, in this case, the performance of an important match. Specifically, athletes completed the research protocol evaluating competitive stressors, cognitive appraisal, and emotions regarding an upcoming match. The variables of the study were organized according to the theoretical lines of the study of human adaptation to stress (Lazarus, 1991,1999;Gomes,2014), namely the factors that can trigger stress in athletes when they are exposed to a critical incident (antecedent variable); the processes of cognitive appraisal (mediator variables); and, the emotional reactions (consequent variables), controlling the influence of the competitive level in these relationships (moderator variable). Materials and methods Participants The study involved 352 male young soccer athletes included in the Portuguese national championship of soccer, with ages for total sample ranging from 15 to 19 years old (M= 16.91, SD = 0.99). In terms of competitive level, 189 (54%) were in the U17 teams (ages between 16 and 17 years old) and 163 (46%) in the U19 team (ages between 18 and 19 years old). Regarding the number of collective titles won by the athletes, 268 (76%) reported at least one title, while 84 (24%) did not obtain any title. The mean of years of practice in official competitions was 9.14 (SD = 2.19), ranging from 1 to 15 years. Measures Sources of stress The Questionnaire of Competitive Stressors in Sport (QCSS; Faria and Gomes,2018) was used to evaluate the potential sources of stress associated with the athletes’ performance. Specifically, athletes were asked to evaluate the level of stress caused by different competitive stressors regarding the upcoming match (0=no stress, 4 =very stressful). The 24 statements were divided into six dimensions (4 items each): (a) competitive readiness: stress related to the athlete’s concern about not being well prepared for competing (e.g., “Not feeling ready for this next match,” αfor this study = 0.77); (b) performance: stress related to athlete’s concern about having a bad performance or a performance below expectations (e.g., “To be defeated or have a bad result in this match,” αfor this study = 0.80); (c) errors: stress related to the athlete’s concern about failing or making mistakes in important moments of competitions (e.g., “To fail in important moments of the match,” αfor this study = 0.86); (d) social expectations: stress related to athlete’s concern related to not corresponding to what is expected of them and receiving negative evaluations from others (e.g., “Not match what others expect from me,” αfor this study = 0.76); (e) opponents: stress related to athlete’s concern about competing with high qualified opponents (e.g., “To play against an opponent that is as good or better than me,” αfor this study = 0.88); and (f) injuries: stress related to athlete’s concern about the possibility of getting injured (e.g., “Getting injured during the match,” αfor this study = 0.73). The final score of perceived stress was computed through the average of the items’ scores of each dimension. Confirmatory factor analysis was performed to test construct validity and the instrument showed Frontiers in Psychology 04 frontiersin.org fpsyg-13-939840 August 24, 2022 Time: 14:11 # 5 Gomes et al. 10.3389/fpsyg.2022.939840 Competitive stressors Primary cognitive appraisal Secondary cognitive appraisal Competitive level Emotional experience FIGURE 1 Proposed model of the study. good psychometric properties in this study: χ2(234) = 594.81, p<0.001; χ2/df = 2.54; RMSEA = 0.066, C.I. [0.060;0.073]; SRMR = 0.073; CFI = 0.919; TLI = 0.904. Cognitive appraisal The Primary and Secondary Cognitive Appraisal Scale (PSCAS; Gomes and Teixeira,2016) was used to evaluate the cognitive appraisal, which is based on Lazarus’s transactional model (Lazarus and Folkman,1984;Lazarus,1991,1999), in the interactive perspective of adaptation to stress (Gomes,2014), and in the model of stress and pressure at work (Karasek, 1979). The instrument consists of 15 items answered on a sevenpoint Likert scale (e.g., 0 = Not at all;6=Very much). It evaluates two dimensions: (a) the primary cognitive appraisal; and (b) the secondary cognitive appraisal. In the first section (primary cognitive appraisal), athletes indicate the importance and personal significance of the match in question, including three subscales (3 items each): (a) importance perception: indicates the importance attributed by the athlete to the upcoming match (e.g., “This match is important to me,” αfor this study = 0.89); (b) threat perception: indicates the extent to which the athlete evaluates the upcoming match as disruptive and negative (e.g., “This match is disturbing to me,” αfor this study = 0.79); and (c) challenge perception: indicates the extent to which the upcoming match is evaluated as stimulating and exciting by the athlete (e.g., “This match is exciting to me,” αfor this study = 0.80). Regarding secondary cognitive appraisal, athletes evaluated the resources they believe they possess to deal with and solve the situation in question, across two dimensions: (a) coping perception: indicates the extent to which the athlete feels he/she has the resources to deal with the demands of the upcoming match (e.g., “I am able to deal and solve the demands of this match,” αfor this study = 0.84); and (b) control perception: indicates the extent to which the athlete feels he/she has the power to decide about what to do in the upcoming match (e.g., “What happens in this match depends on me and my abilities,” α= for this study 0.79). The final score is computed through the mean of the items’ scores in each dimension, with higher values meaning higher scores in each dimension. Confirmatory factor analysis was performed to test construct validity and the instrument showed good psychometric properties in this study: χ2(80) = 139.538, p<0.000; χ2/df = 1.744; RMSEA = 0.046, C.I. [0.033;0.059]; SRMR = 0.044; CFI = 0.975; TLI = 0.968. Emotions The Sport Emotion Questionnaire [SEQ; translated and adapted from Jones et al. (2005)by Faria and Gomes (2018)] was used to access subjective feelings associated with emotions in sport in five dimensions: (a) anxiety (e.g., “I am worried about the next match,” αfor this study = 0.76); (b) dejection (e.g., “I am unhappy about the next match,” αfor this study = 0.92); (c) anger (e.g., “I am infuriated about the next match,” αfor this study = 0.85); (d) excitement (e.g., “I am excited about the next match,” αfor this study = 0.73); and, (e) happiness (e.g., “I am happy about the next match,” αfor this study = 0.93). The first three dimensions assess negative emotional reactions and the last two positive emotional reactions. The instrument consists of 22 items answered on a five-point Likert scale (0 = Not at all to 4 = Extremely). Athletes fulfilled the instrument by thinking about their feelings at that specific moment regarding the upcoming match. The final score is obtained through the mean of the items’ scores of each dimension, with higher values meaning a greater emotional experience of the dimension in question. Confirmatory factor analysis was performed to test construct validity and the Frontiers in Psychology 05 frontiersin.org fpsyg-13-939840 August 24, 2022 Time: 14:11 # 6 Gomes et al. 10.3389/fpsyg.2022.939840 instrument showed good psychometric properties in this study: χ2(178) = 406.185, p<0.000; χ2/df = 2.282; RMSEA = 0.060, C.I. [0.053;0.068]; SRMR = 0.086; CFI = 0.952; TLI = 0.943. Procedure The study was first submitted and approved by the Ethics Committee of the first authors’ University (SECSH-0162015). In this study, a convenience sample was used considering the following inclusion criteria: (a) language (Portuguese speakers), (b) athletes were in conditions to compete in the next upcoming match, and (c) gender (only male players were included), (d) competitive level (part of the U17 or U19 teams), and (e) competitive level (playing in the main division of the national league). Once the clubs accepted to be part of the study, athletes were contacted to participate. Because U17 and U19 teams were chosen, some athletes were underage (below 18 years old). In these cases, permission was first granted from their legal guardians. After legal guardians (when applicable) and athletes agreed to participate, the data collection was scheduled. Data collection followed a critical incident approach (cf. Flanagan,1973;Hettlage and Steinlin,2006), which is a procedure known to facilitate the research of significant occurrences (i.e., critical incidents). Critical incidents are commonly defined as an observable activity that is sufficiently comprehensive to allow inferences and predictions to be made (Bitner et al.,1994). The main aim of this approach is to have a deeper understanding from the individual’s point of view (in this case, of the athlete) regarding the cognitive, affective, and behavioral elements entailed in the situation (Gremler, 2004). Even though this approach is more commonly used in qualitative research, it is also appropriate for quantitative methods to describe the nature of the events and their relationships with other variables (cf. Gremler,2004). Therefore, every data collection was scheduled for 48–24 h before an important match. To ensure that athletes would consider the upcoming match “important,” data was collected during the final stages of the national championship (i.e., stages that define the teams’ final classifications) being also adopted other criteria associated with the values of importance perception of the PSCAS instrument, as explained below. Athletes filled the research protocol in the presence of a research team member. Before answering the research protocol, athletes had to read the study’s instructions and goals and sign the informed consent forms. In the case of underage athletes, the informed consent was signed by their parents or coaches. Next, the athletes answered the evaluation protocol, consisting of the demographic information and the instruments explained below. The questionnaire was completed individually in an appropriate room made available by each sports club. It lasted between 15 and 25 min. Athletes’ participation was voluntary and anonymously, and the confidentiality of the collected data was ensured. Data analysis The first step consisted of analyzing the importance perception dimension of the cognitive appraisal instrument. According to Gomes (2014), adaptation to stress implicates that athletes perceive the potentially stressful situation as important. To ensure it, athletes who scored 2 or less in this subscale were not included in the analysis as they attribute low personal relevance to the game they were about to play. Following this criterion, three participants were removed from the analyses (final n= 352). An online a priori sample size calculator for structural equation models was used to define the appropriate sample size for the proposed model (cf. Soper,2022). A medium effect size of 0.3 and a desired statistical power level of 0.80 at the probability level of 0.05 was used as criteria. Therefore, to test the proposed model, a minimum of 221 participants was recommended. Regarding the statistical assumptions to conduct Structural Equation Modeling, we checked for normality (cf. Kline, 2011) and multicollinearity (cf. Marôco,2014). Regarding the normality assumptions, skewness and kurtosis were assessed. No severe deviations from normality were found (−1.31 >sk <2.16; −0.59 >ku <4.11). Correlations and VIF coefficients were used to assess for the multicollinearity assumption, and no indications of multicollinearity were found (−0.31 >r<0.44; 1.00 >VIF <1.34). Therefore, all assumptions were met. This study’s first analysis aimed to assess athletes’ psychological experience before an important match. To do so, descriptive analyses were conducted to check for the relations among the variables (sources of stress, cognitive appraisal, and emotions). Then, to test H1 (referring to the mediating role of cognitive appraisal in the relationship between competitive stressors and emotions), structural equation modeling was used in AMOS SoftwareR . To ensure that the proposed partial mediation was the model that fit the data best, it was compared against the direct model (where direct relationships from competitive stressors and cognitive appraisal to emotions were included) and the alternative total mediation model (similar to the proposed model but without any direct effects from competitive stressors to emotions included). In order to simplify the models by decreasing the number of parameters to estimate (cf. Marôco, 2014), first-order latent variables were created for the cognitive appraisal (challenge, threat, control, and coping perceptions), and second-order latent variables were created for competitive stressors and for positive (excitement and happiness) and negative (anxiety, dejection, and anger) emotions. To assess Frontiers in Psychology 06 frontiersin.org fpsyg-13-939840 August 24, 2022 Time: 14:11 # 7 Gomes et al. 10.3389/fpsyg.2022.939840 TABLE 1 Means (Standard deviations) and correlations among the study variables (N= 352). M(SD) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Competitive stressors 1. Competitive readiness 1.93 (0.81) 2. Performance 2.32 (0.75) 0.64** 3. Errors 2.24 (0.36) 0.67** 0.70** 4. Social expectations 1.70 (0.85) 0.62** 0.60** 0.65** 5. Opponents 1.04 (0.78) 0.44** 0.30** 0.41** 0.61** 6. Injuries 1.82 (0.88) 0.63** 0.53** 0.52** 0.48** 0.31** Cognitive appraisal 7. Importance perception 5.22 (0.02) 0.09 0.24** 0.17** 0.09 −0.01 0.12** 8. Threat perception 1.34 (1.28) 0.21** 0.15** 0.24** 0.27** 0.31** 0.17** −0.21** 9. Challenge perception 4.92 (1.15) 0.07 0.12*0.12*0.04 0.01 0.02 0.64** −0.12* 10. Coping perception 5.10 (0.77) −0.13*0.06 −0.14** −0.18** −0.24** −0.11*0.37** −0.28** 0.27** 11. Control perception 4.07 (1.11) −0.12*−0.02 −0.09 −0.11*−0.03 −0.09 0.20** −0.05 0.16** 0.42** Emotions 12. Anxiety 1.16 (0.78) 0.25** 0.23** 0.32** 0.30** 0.31** 0.17** 0.08 0.34** 0.15** −0.23** −0.07 13. Dejection 0.47 (0.87) 0.16** 0.10*0.01 0.15** 0.01 0.12*−0.20** 0.20** −0.22** −0.15** −0.10 0.21** 14. Anger 0.49 (0.81) 0.15** 0.12*0.01 0.15** 0.13*0.12*−0.12*0.21** −0.13*−0.14** −0.05 0.32** 0.81** 15. Excitement 2.86 (1.03) 0.00 0.11*0.08 −0.06 −0.12*−0.02 0.43** −0.14** 0.46** 0.25** 0.17** 0.17** −0.23** −0.12* 16. Happiness 2.69 (0.90) −0.02 0.05 0.01 −0.06 −0.02 0.03 0.35** −0.17** 0.34** 0.13*0.17** 0.05 −0.59** −0.47** 0.55** *p<0.05; **p<0.01. Frontiers in Psychology 07 frontiersin.org fpsyg-13-939840 August 24, 2022 Time: 14:11 # 8 Gomes et al. 10.3389/fpsyg.2022.939840 the quality of the mediation models, the following criteria were used: (a) chi-square statistics (χ2); (b) Root mean square error of approximation (RMSEA; Steiger,1990), considering an adequate fit when its values rely upon between 0.05 and 0.08 and a good fit when below 0.05 (cf. Arbuckle,2008); (c) Standardized root mean square residual (SRMR) for which a good fit is achieved when below 0.10 (cf. Kline,2011); (d) Tucker-Lewis index (TLI; Bentler and Bonett,1980) and Comparative fit index (CFI; Bentler,1990), for which values between 0.90 and 0.95 indicate an adequate fit and above 0.95 a good fit (cf. Bentler,2007;Marôco,2014). Bootstrap analyses were conducted to calculate the total and indirect effects of the mediation model. Finally, to test H2, which analyzed the moderating role of the competitive level in the relationship between competitive stressors, cognitive appraisal, and emotions. Indirect effects and moderation analysis were conducted on AMOS SoftwareR using bootstrap technique and multigroup modeling (cf. Marôco, 2014), respectively. The same criteria for the mediation model were used to assess the model fit. Results Descriptive statistics Table 1 summarizes the descriptive statistics of the study variables (stressors, cognitive appraisal, and emotions) and the correlations among them. Regarding the stressors, it can be concluded that performance and errors are the most prevalent, while opponents are the weaker source of stress for athletes. In cognitive appraisal, athletes seem to have a higher tendency to perceive the game more as a challenge than a threat and as having the necessary resources (control perception) to deal with it. Regarding the intensity of emotions, happiness and excitement seem to be the most prevalent compared to anxiety, dejection, and anger. Regarding the correlations, all stressors are positively related to each other and with threat perceptions. Only performance and errors, as sources of competitive stress, are positively correlated with challenge perceptions. Most stressors are also negatively related to coping perception and positively to negative emotions (anxiety, dejection, anger). Competitive readiness and social expectations are negatively related to control perception. On the other hand, performance was positively related to excitement (positive emotion), and opponents were negatively related to the same positive emotions. Concerning the relationship between cognitive appraisal and emotions, threat perception was positively related to negative emotions and negatively related to positive emotions. On the other hand, the more athletes perceived the competition to be a challenge, the more positive their emotions (excitement Competitive stressors Threat perception Challenge perception Control perception Coping perception Positive emotions (R 2 = .15) Negative emotions (R 2 = .33) FIGURE 2 Direct model’s standardized coefficients. *p<0.05; **p<0.01; only significant paths are displayed. and happiness), the higher their anxiety, and the lower their negative emotions (dejection and anger). Coping and control perceptions were also positively related to positive emotions. The coping perception was also found to be negatively related to negative emotions. Stressors and emotions: The mediating role of cognitive appraisal To analyze the mediating role of cognitive appraisal in the relationship between competitive stressors and emotions, three different models were tested: (1) the direct model, which establishes a direct relationship between competitive stressors and cognitive appraisal of negative and positive emotions (cf. Figure 2); (2) the partial mediation model, including relations from competitive stressors to cognitive appraisal and emotions, but also direct relations from cognitive appraisal to emotions (cf. Figure 3); and (3) the total mediation model, which is similar to the previous model but no direct relations from competitive stressors to emotions were included (cf. Figure 4). Table 2 summarizes the fit indexes obtained from the three models. The one that presents the best fit to the data is the partial mediation model. A chi-square test was conducted to assess the differences in the model fit. The results showed that the partial mediation model has a significantly better fit to the date than the total mediation model (1χ2= 9.92; 1df = 2; p= 0.007), and then the direct model (1χ2= 97.88; 1df = 8; p<0.001). This result supported H1, meaning that the cognitive appraisal Frontiers in Psychology 08 frontiersin.org fpsyg-13-939840 August 24, 2022 Time: 14:11 # 9 Gomes et al. 10.3389/fpsyg.2022.939840 Competitive stressors Threat perception ( R 2 = .10 ) Challenge perception ( R 2 = .01 ) Control perception ( R 2 = .07 ) Coping perception ( R 2 = .17 ) Positive emotions ( R 2 = .37 ) Negative emotions ( R 2 = .17 ) .27** FIGURE 3 Standardized coefficients of the partial mediation model. *p<0.05; **p<0.01; only significant paths are displayed. mediated the relationship between competitive stressors and emotions. According to the results, this mediation was partial. Thus, the partial mediation model’s coefficients were further analyzed. The model explained the variance of the perception of threat by 10%, challenge perception by 1%, control perception by 7%, and coping perception by 17%. Moreover, 17% of the negative emotions’ variance and 37% of positive emotions’ variance were explained by the predictor and mediator variables. The direct effects (cf. Figure 3) showed that athletes who feel higher levels of competitive stressors also perceive higher threats about the upcoming match, experience lower perceptions of control, and stronger negative emotions. It was also found to have direct effects between perceiving higher threats and less coping and the experience of less positive emotions and more negative emotions. On the other hand, higher perceptions of challenges contribute to higher control and coping perceptions and more positive and less negative emotions. A positive direct effect between coping perception and positive emotions was also found. The indirect and total effects are displayed in Table 3. The effect of primary cognitive appraisal on emotions was mediated by secondary cognitive appraisal. Specifically, higher threat levels predicted lower control and coping perceptions, which, in turn, lead to lower positive emotions. On the other hand, higher perceptions of challenges lead to higher perceptions of control and coping perception, which, in turn, predict more positive emotions. Multigroup analysis: Model comparison amongst U17 and U19 This analysis aimed to compare the model with the best fit (partial mediation model) amongst U17 and U19 competitive levels. The central assumption was that the model would be invariant and that the model would behave similarly for both groups. The first step consisted of comparing the invariance of the measurement model for the two groups; this was done by comparing the model with fixed weights against the unconstrained model (i.e., the model with all parameters free). 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